Papers

Artificial intelligence (AI) is transforming materials discovery, yet conventional data-driven approaches often suffer from limited interpretability, poor extrapolation, and inconsistency with physical laws. Since materials behavior is fundamentally governed by thermodynamics, kinetics, electronic structure, transport processes, and operating environments, the next generation of materials intelligence must move beyond correlation-based prediction toward physics-grounded reasoning. In this Perspective, we systematically discuss Physics-Grounded Materials AI (PhysMat AI) as a unifying perspective for integrating physical knowledge into materials intelligence through five complementary roles: physics as prior knowledge, descriptors, constraints, verifiers, and infrastructure. Using representative examples from catalysis, solid-state electrolytes in solid-state battery, and hydrogen-storage materials, we illustrate how physical principles guide data representation, model reasoning, validation workflows, and knowledge management. We further present how AI agents can leverage these physics-aware components to perform mechanism-guided discovery within physically feasible search spaces. Finally, we outline a developmental roadmap from physics-aware AI to physics-reasoning AI and ultimately physics-autonomous AI. Looking forward, materials intelligence should evolve from predictive models toward autonomous scientific systems capable of integrating physical reasoning, multiscale simulations, experimental validation, and continuous knowledge updating for reliable materials discovery.

We systematically investigate the different coefficients of restitution of a dissipative, frictional disc as a function of the impact angle $\theta$, the friction coefficient $\mu$ and initial rotation $\omega_{\mathrm{in}}$. We observe a non-monotonic, non-linear behaviour of $e_{\mathrm{T}}$ and $e_{\mathrm{kin}}$ with a clear minimum at $\mu$-dependent values of $\theta$ and a convergence for all $\mu$ at large $\theta$, bounded by the cases of pure rolling and pure sliding. Changing the dissipative normal interaction affects the $\mu$ convergence at large $\theta$ and leads to a convergence at low $\theta$. The presence of initial angular velocity $\omega_{\mathrm{in}}$ can significantly alter the functional behaviour of $e_{\mathrm{T}}$ at steep impacts and slightly change the magnitude of $e_{\mathrm{kin}}$, with friction playing only a minor role. Overall, our results indicate that any specific value of $e_{\mathrm{T}}$ or $e_{\mathrm{kin}}$ is highly situational and can simultaneously describe entirely different contact configurations.

The coupled-cluster (CC) equations are most frequently solved via fixed-point (FP) iterations. However, when formulated in a non-canonical gauge, as in local correlation CC, the FP iteration may converge slowly or even diverge. Practical fixes, such as level-shifting and a direct inversion of iterative subspace (DIIS), often improve the convergence, but remain fundamentally heuristic and gauge dependent. Yang et al.~demonstrated that preconditioned Newton–Krylov (PNK) methods provide substantial wall-time advantage for canonical CC. In this work, we generalize the preconditioner to arbitrary gauges by replacing the energy denominator with a gauge-invariant formulation. Combined with Krylov-based approximate Jacobian inversion, the resulting framework removes the need for level-shifting and yields robust and efficient convergence across various gauges and challenging chemical systems. Our numerical results indicate that PNK consistently outperforms carefully optimized FP-based approaches across a range of molecular systems, positioning the proposed PNK method as a promising new standard for solving the CC equations.

We present a detailed chemical analysis of seven extremely metal-poor (EMP) star candidates observed with X-Shooter, combining them with 16 EMP candidates from Paper I. We measured abundances for 16 elements, showing excellent agreement with previously published results. The sample was further extended using high-resolution literature data for 315 metal-poor stars. The full sample was then kinematically separated into prograde disk, retrograde disk, Gaia-Sausage Enceladus (GSE) and halo classifications. Combining dynamics with chemistry, we demonstrate that the prograde disk exhibits a distinct negative linear trend in [Sc/Mg] with increasing metallicity, with a slope of -0.6 dex per dex. This contrasts with the halo trend at -0.04 dex per dex, a difference significant at the 3.95$\sigma$ level. Within the metallicity range -4.2 $\leq$ [Fe/H] $\leq$ -1.9, the prograde disk trend is driven by low [Mg/Fe] at lower metallicities, along with low [Sc/Fe] at higher metallicities. This could be due to reduced early Mg enrichment in the progenitor prograde disk, followed by subsequent Mg enrichment, possibly associated with a later gas accretion event. However, the physical origin of the higher-metallicity Sc depletion remains unexplained by current nucleosynthesis models. The result remains significant at the >3$\sigma$ level across kinematic classifications derived from a different Galactic potential. Additionally, we also identified an r-I star with enhanced Ti, moderately-enhanced Sc, and depleted in C (unrelated to its evolutionary state). These abundances suggest a massive jet-induced hypernova progenitor, though a measurement of Zn is needed to verify this.

Foundation machine-learning interatomic potentials (MLIPs) enable atomistic simulations at substantially lower computational cost than first-principles methods, but their reliability across structural geometries remains insufficiently understood. Here, we construct a density-functional-theory dataset of ZrO2 configurations spanning bulk, slab, particle, neck, and atomically thin wire environments motivated by an experimentally observed ZrO2 desintering process involving neck thinning and atomic wire formation. We first benchmark 26 pretrained MLIPs and observe pronounced geometry-dependent degradation in zero-shot predictions. Without any training, after only reference-energy alignment, the best zero-shot model (ORB-V3) reaches energy and force root-mean-square errors of 6 meV/atom and 197.3 meV/Å, respectively, with the largest force errors in neck and wire configurations. We then compare zero-shot inference, fine-tuning, and training from scratch strategies. Fine-tuning yields lower energy and force errors than training from scratch, while both require comparable wall-clock time. Geometry-specific fine-tuning improves in-domain accuracy but frequently produces negative transfer to other structural classes, whereas mixed-geometry fine-tuning reduces cross-geometry errors. Evaluations of elastic and vibrational properties, surface energies, and neck dynamics further show that rankings based on average energy and force errors do not universally predict property-level behavior. These results demonstrate that geometry-diverse target data and independent physical validations are necessary when adapting foundation MLIPs to low-coordination (ionic) nanostructures.

We present the design, development, and first calibration results of a compact beta electron detector for the Quantum Invisible Particle Sensor (QuIPS) experiment. The QuIPS electron detector is designed to reconstruct the full momentum vector of $\beta$ particles emitted from radioisotope-doped optically levitated nanospheres in ultra-high vacuum (UHV), enabling a measurement of the neutrino momentum and a search for heavy sterile neutrinos. The detector comprises two thinned CMOS detectors for directional tracking and a plastic scintillator read out by silicon photomultipliers (SiPMs) for calorimetry. The entire assembly must operate inside an existing optical trapping vacuum chamber at pressures below $10^{-7}$ mbar, imposing stringent constraints on material selection, power dissipation, outgassing, and compactness. We demonstrate sensitivity to $\beta$-decay electrons with energies as low as 100 keV and a detection efficiency of 35% above 500 keV, the primary window of interest for a heavy sterile neutrino search. The CMOS tracker resolves the momentum direction at the mrad scale and reconstructs the $\beta$ emission vertex with sub-mm precision, while the scintillator-SiPM system achieves an energy resolution of 5% at 1 MeV.

A finite group-valued temporal reference frame defines a correlated random-unitary process rather than a list of independent channels. We identify a regime in which its complete trajectory law is an exact operational coordinate. If the carrier contains every irreducible representation of the finite group $G$, one ancilla-assisted input resolves all group elements, and for arbitrary laws $\mu,\nu$ on $G^n$ the strategy half-distance equals $d_{\mathrm{TV}}(\mu,\nu)$. Optimal output-side causal post-processing likewise reduces to classical convolution on $G^n$. This converts temporal hiding into a $q$-ary coding problem. Uniform coset laws of an $[n,k]_q$ code are identical on every set of fewer than $d(C^\perp)$ slots and perfectly distinguishable globally. For $M$ sectors with leakage at most $\eta$ from $t$ selected slots and global decoding error $\epsilon$, we obtain $(1-\epsilon)\log M \leq (n-t)\log q+\eta+h_2(\epsilon)$. For nested codes $C\subset D$, the payload $R=\dim D-\dim C$, invisible depth $t=d_{\mathrm{rel}}(C^\perp,D^\perp)-1$, and sector distance $d_{\mathrm{rel}}(D,C)$ obey $R+t+d_{\mathrm{rel}}(D,C)-1\leq n$ and $R+t+2e+f\leq n$, where $e$ and $f$ are adversarial errors and known erasures. Nested generalized Reed-Solomon codes attain the bounds in their existence range. We also give the exact projection-rank leakage profile and show that hiding arbitrary coherent superpositions from $t$ slots is precisely quantum erasure correction, yielding $\log_q K+2t\leq n$. The results separate classical trajectory privacy from coherent temporal privacy and quantify the robust payload hidden from reduced process tomography.

We describe the development, validation and implementation of a Quantum Interactive Learning Tutorial (QuILT) on quantum key distribution (QKD) using entanglement, a context which involves a practical application of quantum concepts relevant for the second quantum revolution. The QuILT helps students learn quantum concepts relevant for quantum cryptography using a simple two-particle system. The protocol uses two entangled particles and two Stern-Gerlach Apparati to generate a random shared key over a public channel for encrypting and decrypting information. It actively engages students in the learning process and helps them build links between the concepts learned in class and their real world applications. The QuILT was implemented as a homework in a traditional quantum mechanics course and a quantum computing and quantum information course. The evaluation suggests that the QuILT is helpful in improving students' understanding of the concepts related to QKD in both courses. Also, the evaluation of the QuILT in both types of courses with or without lecture-based instruction in relevant QKD concepts suggests that the QuILT can be given as a homework after lecture-based instruction on entanglement without in-class discussion on QKD. Therefore, entanglement can be covered without taking up much in-class time, while also providing students with an understanding of the QKD method and how it protects from eavesdroppers.

Erosion-induced landslide mobility is a prominent phenomenon in nature. However, this topic remains poorly understood, even though erosion greatly alters nearly every aspect of landslide mechanics, dynamics, run-out, mobility, deposition structure and the enormous destructive power carried by such catastrophic events. Here, I present a simple, elegant, and exact analytical model describing the kinematics of erosion-induced landslide mobility in terms of a newly constructed mobility controller containing essential forcing mechanisms in erosion. In contrast to the classical perspective, I formally prove that, irrespective of how large the erosion rate is, the erosion rate alone is not sufficient to determine enhanced or reduced mobility; mobility is also greatly regulated by the volume bulking rate, erosion drag or thrust, and flow depth. With this mechanical mobility controller, it is now possible to explain precisely when the mobility of an erodible landslide is enhanced or reduced. I demonstrate that, a mechanically valid, physically founded erosion model must be able to explain both the enhanced and reduced mobility of erosive landslides.

The law of conservation of energy can be stated: Energy can neither be created or destroyed but only converted to from one form to another. Laboratory experiments demonstrating that no energy is lost or gained during a conversion have been rare. Interestingly, there is a close connection between energy conservation, Lorentz violation and the possibility of a second dimension of time. We explore this connection within a model of Lorentz invariance that incorporates a second dimension of time. The model's Lorentz transformation matrix reduces to the well-known one-dimension of time version in the limit of a parameter that defines the relative size of the extra dimension. If the parameter is finite, one might misinterpret the energy equivalence of mass or observe a deviation from the accepted time dilation formalism. We explore different experimental limits on this new parameter including Lorentz violating parameters from the Standard-Model Extension.

This study applies Duan's topological current $\phi$-mapping theory to investigate a newly proposed charged modified AdS black hole using the Rényi entropy formalism, examining its thermodynamic properties across the canonical, mixed, and grand canonical ensembles.} Electric and magnetic charges are fixed in the canonical ensemble, whereas the mixed ensemble incorporates electric and magnetic potentials. The grand canonical ensemble, meanwhile, ensures consistency by employing these potentials exclusively. Initially, we compute topological charges by identifying critical points in each ensemble. In both the canonical and mixed ensembles, we identify a conventional critical point with a topological charge of $-1$. We then model the black hole's domain in the AdS regime as a topological defect in thermodynamic space and analyze its local and global topology by calculating the winding numbers at these defect locations. {Interestingly, the canonical and mixed ensembles exhibit identical black hole topologies, each possessing a total topological charge of $1$ within the framework of the Rényi entropy.} Finally, we characterize the canonical, mixed, and grand canonical ensembles based on the presence of generation/annihilation points: the canonical ensemble has one such point, the mixed ensemble has a negative one, and the grand canonical ensemble has none.

Accurate prediction of vapor–liquid equilibrium (VLE) for hydrocarbon-nitrogen mixtures remains challenging for cubic equations of state, particularly across broad ranges of composition and hydrocarbon chain length. While deep learning models can provide accurate predictions, they often lack interpretability and explicit analytical expressions. In this work, we propose a symbolic machine learning approach to discover interpretable symbolic corrections to Peng-Robinson equation-of-state (PR-EOS) predictions from experimental data. The proposed approach adopts a two-level strategy: symbolic expressions are first identified for individual hydrocarbon systems, after which their coefficients are represented as functions of carbon number to enable accurate prediction across different hydrocarbon systems. The results demonstrate significantly improved prediction accuracy over the original PR-EOS across all hydrocarbon-nitrogen systems. Overall, the proposed approach provides an interpretable symbolic correction framework for improving PR-EOS predictions of hydrocarbon-nitrogen VLE.

Accurate solar irradiance forecasting is essential for the reliable integration of photovoltaic power into modern electricity grids. All-sky imagers (ASI) provide high-resolution observations of clouds, making them well suited for intra-hour forecasting. Recent deep learning approaches have substantially improved forecast accuracy but are often limited by deterministic predictions and a reduced capability to anticipate ramp events. This work proposes FarSky, a generative forecasting framework that leverages latent-space coupling to learn task-aware representations of sky images. A multi-task autoencoder first learns a shared latent representation for image reconstruction and irradiance estimation. A latent diffusion model then generates future latent states conditioned on recent observations, from which irradiance forecasts are directly decoded. Probabilistic forecasts are inherently obtained through stochastic sampling. The framework is developed using a multi-year ASI dataset acquired at the Plataforma Solar de Almería, Spain, and evaluated on two independent test datasets against persistence, state-of-the-art end-to-end, and generative forecasting approaches. FarSky achieves the best overall deterministic and probabilistic forecasting performance, improving forecast skill by up to 11 percentage points. Furthermore, it substantially improves ramp event detection over existing methods, achieving F1-scores above 60%. These results demonstrate the potential of combining generative models with task-aware latent-space coupling for solar forecasting.

The in-Situ Thunderstorm Observer for Radiation Mechanisms (iSTORM) is a gamma-ray spectrometer to study gamma-ray transients originating from thunderstorms, such as glows and terrestrial gamma-ray flashes (TGFs). It is designed and built by the U.S. Naval Research Laboratory for deployment aboard a NASA ER-2 aircraft. Using an array of 32 one-inch-diameter $\mathrm{CeBr}_3$ scintillators read out with silicon photomultipliers (SiPMs), the instrument achieves an energy range of $\sim 250 \ \mathrm{keV}$ to $5 \ \mathrm{MeV}$ under flight conditions, with a total geometrical area of $157 \ \mathrm{cm^2}$. One of two gamma-ray instruments in the ALOFT campaign, iSTORM recorded glows, terrestrial gamma-ray flashes (TGFs), and the newly discovered flickering gamma-ray flashes (FGFs).

The transition to automated transportation introduces mixed-autonomy traffic where human drivers may strategically exploit the risk-averse behavior of Connected and Automated Vehicles (CAVs). While microscopic models capture these dyadic interactions, their aggregate impact on network-level stability remains unquantified due to the scale gap between agent-based and continuum models. This study bridges this analytical divide by integrating a game-theoretic friction term directly into the macroscopic kinematic wave framework. We model the cut-in maneuver as a Stackelberg game, identifying a distinct "exploitation window" where human drivers leverage CAV defensiveness to execute aggressive merges. By deriving a closed-form micro-macro bridge, we translate these discrete strategic outcomes into a continuous friction parameter that endogenously modifies the traffic conservation law. Theoretical analysis and numerical simulations confirm that this behavioral asymmetry functions as a deterministic destabilizer, generating perturbation source terms that trigger phantom jams and strictly reduce road capacity. Crucially, we reveal a convex relationship between CAV penetration and system efficiency, identifying a critical instability regime at intermediate penetration rates (approximately 45 percent) where the frequency of exploitable interactions is maximized. These findings demonstrate that without socially aware control policies, the defensive nature of early-deployment CAVs may paradoxically degrade traffic flow stability.

Ice I admits cubic, hexagonal, and mixed layer stackings, but rigorous comparisons of its proton configurational entropy have focused on the two ideal endmembers. We identify every cyclic uniform-registry ice-I stacking with a word in a nonnegative layer-transfer operator and its transpose. Applying the Schatten-Hölder inequality to every even-length word proves that alternating hexagonal stacking maximizes the ice-rule configuration count at each common finite cross-section. Consequently, hexagonal ice maximizes the thermodynamic configuration constant among all periodic uniform-registry ice-I polytypes. We also construct rigorous lower and upper bounds without finite-size extrapolation. Restricting Nagle's positive even-subgraph expansion to disjoint blocks gives the lower bound; Finner's hypergraph Hölder inequality and rational Collatz-Wielandt certificates for two-replica prism operators give the upper bounds. The resulting configuration constant $w$, whose logarithm is the entropy per molecule in units of Boltzmann's constant, satisfies $1.503360 \le w \le 1.540196$, with the sharper cubic-ice ceiling $w \le 1.527699$. The same bracket controls lower and upper configuration growth rates of fixed aperiodic stackings along the specified prism-tileable exhaustions. These results establish hexagonal stacking as a possibly nonunique maximizer; equality of the cubic and hexagonal entropy constants remains unresolved.

Recent advances in realizing nearly degenerate dipolar gases in optical lattices have enabled the study of quantum systems with long-range anisotropic interactions. Here, we investigate hard-core dipolar bosons on a two-dimensional square lattice described by an extended Bose–Hubbard model. Using path-integral quantum Monte Carlo simulations at fixed azimuthal angle $\varphi=45^\circ$, we investigate density instabilities arising from first-order phase transitions. We start by mapping the ground-state phase diagram at half filling as a function of dipolar interaction strength and polar angle $\theta$. For weak interactions, the system remains superfluid for all $\theta$. Above a critical interaction strength, the superfluid phase becomes unstable and gives way to checkerboard, stripe, or incompressible phases depending on $\theta$. For $\theta\gtrsim 62^\circ$, we find that half filling becomes unstable and only the empty state, $n=0$, and the fully filled state, $n=1$, are stable. Unlike recent experimental reports of a self-bound insulator at half filling, the homogeneous ground state does not support such a phase, but instead exhibits a direct first-order transition between $n=0$ and $n=1$. At finite temperature, thermal fluctuations shift the onset of density instabilities to larger $\theta$ and stabilize intermediate fillings in the regime where half filling is unstable in the ground state. This leads to phase-separated states consisting of empty and fully filled regions that resemble the experimentally observed "self-bound insulator." In a harmonic trap, similar structures also emerge from phase coexistence associated with the underlying first-order transition.

We construct, numerically validate, and phenomenologically constrain a pipeline connecting a spontaneously CP-violating ultraviolet Type-I seesaw boundary condition to Planck-suppressed corrections of the T-violating oscillation asymmetry and the CP asymmetry in a minimal 3+1 sterile-neutrino framework. The ultraviolet Yukawa structure is reconstructed via Casas-Ibarra parameterization, matched onto the Weinberg operator at seesaw thresholds, and evolved to the electroweak scale using one-loop RGEs. The renormalized operator is combined with a 3+1 sterile sector to build the oscillation Hamiltonian, with Planck-suppressed terms treated perturbatively to yield closed-form first-order corrections. We report three substantive implementation errors identified and corrected during independent module validation. Running transports ultraviolet flavor structure with high fidelity distorting mixing angles and phases at or below the per-mille level despite an overall flavor-blind operator normalization run of about fifty percent. Subjecting the ultraviolet texture to a four-channel phenomenological suite (muon to electron gamma, tau to muon gamma, tau to electron gamma, non-unitarity, and perturbativity) confines the correction to the range between three in one hundred million and three in ten million at the natural scale. We prove the asymmetry correction is exactly independent of Casas-Ibarra angles at all allowed points, affecting the correction only indirectly via allowed heavy spectra. Sterile sector effects are strongly texture-dependent, ranging from suppression to a forty-fold enhancement. Evaluating the corresponding antineutrino Hamiltonian for the CP asymmetry, we find the Planck-induced correction lies two to three orders of magnitude below DUNE's published CP-phase sensitivity floor. We present this as a checked, reproducible negative phenomenological result.

We revisit the coupling of continuum thermodynamics and electromagnetic theory for polarisable and magnetisable matter in motion. Two routes are followed and then compared. The first route is the axiomatic bulk theory of Dreyer, Guhlke and Müller, in which universal balance laws are closed by an entropy principle. We show that the source of the internal energy balance must be built with the non-convective electric current, that the polarisation current and the Lorentz magnetisation enter through one single identity, which Dreyer et al.\ do not write down, and that this identity fixes both the admissible entropy variables and the signs of the bound-current ansatz. The second route is the statistical-mechanical one of Mazur, in which the macroscopic Maxwell equations are obtained by ensemble averaging over a system of atoms with internal charge carriers. Mazur stops before the conservation laws, so we derive them, and we estimate the size of the mass-correction terms that appear. The comparison shows that after a redefinition of polarisation and magnetisation the two sets of equations agree structurally. The only irreducible difference is a momentum contribution from microscopic field fluctuations, which can not be reproduced in a purely macroscopic theory. We further show that the electromotive intensity $\mathcal{E}$ and the Lorentz magnetisation $\mathcal{M}$ are not modelling choices but appear by themselves, and that the asymmetric look of the entropy function is a consequence of the chosen energy variable and not a defect of the theory.

The DRAMA framework was originally developed at the Anglo-Australian Observatory (AAO) in the early 1990s, with its first release in 1992. Designed in C and C++, DRAMA provides a distributed, message-based control architecture that has powered major instruments such as the 2dF fibre positioner, fibre-fed spectrographs like AAOmega and HERMES, and the IRIS2 infrared imager on the Anglo-Australian Telescope, and the TAIPAN instrument on the UK Schmidt Telescope. Despite its age, DRAMA remains a robust and well-structured system whose real-time behaviour and modular task oriented design continue to be valuable for astronomical instrumentation. As new instruments are being developed at the AAO, we are extending and adapting the DRAMA environment to meet the current software engineering and deployment requirements. Our recent improvements include containerising DRAMA using Docker and a modern Python interface that enables integration without modifying the underlying codebase. This approach preserves the reliability of the original framework, and allows new instruments to adopt DRAMA within more flexible and maintainable ecosystems. At present, DRAMA continues to play an active role in our development efforts: it is being used for the newly built KSPEC spectrograph on the KMTNet telescope, and also forms the control architecture for the high-resolution spectrograph being developed for the Devasthal Optical Telescope.

Direct imaging measures how bright a planet appears in reflected starlight, but brightness alone cannot tell whether the planet is large and dark or small and bright. This radius-albedo degeneracy limits the characterization of non-transiting exoplanets, including those targeted by the Habitable Worlds Observatory (HWO). From multi-epoch observations we construct ultraviolet observables that are independent of planetary radius: the normalized 400 nm lightcurve shape, the ultraviolet intensity and polarization colors, and the degree of linear polarization. In a clear 360-400 nm spectral window where Rayleigh scattering is strong and bright ultraviolet surfaces are nearly colorless, these observables constrain the atmospheric column, the surface reflectivity, and, when relevant, the observed phases before radius is inferred. Using the GPU accelerated vector radiative transfer model vSmartMOM, we test how uniquely these radius-free observables determine the scattering state at signal-to-noise ratios (SNRs) of 5, 20, and 100. For the chosen six phase sequence, spectropolarimetry gives median radius consequences of 9.5%, 3.3%, and 0.45% when the phases are known. If the phases are unknown, six distinct epochs keep the penalty modest at low SNR and negligible at moderate-high SNR, with median consequences of 14%, 3.2%, and 0.47%, respectively. Removing polarimetry degrades the result, especially in the HWO simulations where phase coverage is restricted by inner working angle. For solar twin systems at 6 and 12 parsecs, the required six-phase campaigns fall in the allotted range of a few hundred hours, making this a clear observing path to planetary radii from HWO's reflected-light detections.

The ability to control the $g$-factors of orbital spin states in optically active quantum dot molecules (QDMs) is a prerequisite for the high-fidelity generation of multi-photonic cluster states with higher-dimensional entanglement structure. Protocols that rely on two coupled spins require knowledge of the $g$-factor and its dependence on external control parameters. Mismatches in the $g$-factor between tunnel-coupled dots introduce unwanted dephasing of coupled spin-states, making precise characterization and voltage control essential. Here, we measure the gate voltage dependence of the electron and hole $g$-factors of negatively charged trions $X^{-}$ in a single InGaAs QDM using polarization-resolved magneto-photoluminescence spectroscopy. The electron $g$-factor exhibits a pronounced step-like change at the tunneling resonance, shifting from $g_\mathrm{e} = -0.336\pm 0.008$ to $g_\mathrm{e} = -0.389\pm 0.003$, providing a direct spectroscopic fingerprint of molecular orbital formation and a shift of the wavefunction localization from the lower to the upper dot. In contrast, the hole $g$-factor remains nearly constant at $g_\mathrm{h} \approx 0.094 \pm 0.007$, exhibiting a weak modulation near the anticrossing voltages attributed to Coulomb-mediated deformation of the wavefunction by the tunneling electron. Our results are quantitatively reproduced by an eight-band $\mathbf{k}{\cdot}\mathbf{p}$ model, establishing electric-field control of the trion $g$-factors as a practical tool for independently tuning the Zeeman splitting of individual dots and opening new pathways towards the deterministic generation of two-dimensional photonic cluster states.

Electrical transport measurements reveal that many 2D materials exhibit anisotropic conductivity. However, current methodologies for rectangular geometries can only extract a partial conductivity tensor or are difficult to execute experimentally. Here, we propose a simple experimental procedure to extract the full conductivity tensor (or the resistivity tensor by inversion) including the principal axes angle. Our procedure is developed by using a conformal mapping approach to obtain an analytical expression for the potential with a point source and drain on the perimeter. Our solution agrees very well with numerical simulations using COMSOL and the known limiting case where the principal axes angle vanishes. Finite source/drains can be modeled using superposition.

We construct a nonlinear electrodynamics (NLED) model for a static magnetic black hole. Rather than imposing a regular center, we require a Maxwell weak-field limit, finite magnetic self-energy, a positive and subluminal electromagnetic cone, the standard energy conditions, and a static exterior that satisfies known sufficient stability criteria. A positive mixture of power kernels restricts the exponent to $1/4<\gamma\leq1/2$. For the minimal two-kernel model, with $\gamma_1=1/3$ and $\gamma_2=1/2$, the field equations admit an exact solution in terms of incomplete beta functions. For the branches with nonnegative Schwarzschild mass parameter $M_0$, the metric function is strictly increasing, so there is at most one positive-radius horizon and no inner Cauchy horizon. We construct the maximal extension and show that the black-hole, horizonless, and critical branches have spacelike, timelike, and null singularities, respectively. The representative black-hole families have positive temperature and negative fixed-charge heat capacity. Electromagnetic waves split into ordinary and extraordinary optical branches. We calculate their photon spheres, shadow radii, instability rates, and illustrative Event Horizon Telescope size bands. We also construct ISCO-truncated thin-disk images. The full images remain close, but jointly normalized residual maps and radial profiles reveal a coherent branch-dependent shift near the lensed inner edge and the critical region. The extraordinary branch moves the critical curve outward and partly compensates the shadow reduction caused by magnetic charge.

Understanding and mitigating noise in two-level quantum systems is essential for achieving high-fidelity qubit control. Conventional frequency tracking techniques, such as Ramsey interferometry, are fundamentally limited by trade-offs between sensitivity, bandwidth, and dynamic range. Here we introduce the adiabatic tangentially-modulated (ATM) pulse, a pulse derived from quantum adiabatic theory that maps qubit detuning onto a sigmoidal, near-binary response. Using numerical simulations supported by analytical modeling, we show that pulse sensitivity and detuning range can be independently engineered through simple design parameters. We derive scaling relations governing these quantities and demonstrate their agreement with simulation. A single-shot ATM measurement achieves sensitivity comparable to that obtained from multi-shot Ramsey averaging, enabling tracking of substantially higher frequency noise components with a lower closed-loop white-noise floor. In addition, this pulse exhibits strong robustness to amplitude fluctuations compared with binary response pulses derived from the Shinnar-Le Roux formalism. Together, these properties establish the ATM pulse as a promising approach for robust qubit frequency tracking.

GW231123 is an exceptional gravitational wave event for which different waveform models yield significantly different inferred source parameters. Residual tests provide a direct way to assess whether each waveform model gives an adequate description of the observed signal. In this work, we extend the conventional residual-test methods by subtracting the 100 highest likelihood waveforms, rather than only the maximum likelihood waveform for each model, thereby propagating waveform reconstruction uncertainty into the residual analysis. This ensemble-based approach turns the residual test from a single waveform diagnostic into a robustness test over the local high likelihood waveform manifold. We further perform injection tests to quantify the detectability of cross-model waveform discrepancies in realistic detector noise. The large-scale implementation of these analyses is made possible by the high speed and low computational cost of our residual testing framework, which is based on three goodness-of-fit tests: the Kolmogorov-Smirnov test, the Anderson-Darling test, and Pearson's chi-squared test.

The self-similar growth of massive galaxy clusters suggests that radial profiles of their key thermodynamic properties should have identical shapes after proper mass- and redshift-dependent re-scaling. This property, tested within the virial radius on samples of well-studied individual objects, together with clear and robust observational characteristics such as sensitivity and background accounting, enables the possibility of stacking observations that can be confronted with identically-derived population-averaged predictions from theory or numerical simulations at large radii. Such a comparison not only eliminates effects of inevitable stochasticity in properties of individual objects, but also allows one to reach higher sensitivity for the faintest regions on the outskirts of the clusters. In this study, we conduct a one-to-one comparison of the observed and simulated average soft X-ray surface brightness profiles of several dozen massive galaxy clusters at low redshift. We find a very good out-of-the-box agreement between the 0.3 - 2.3 keV surface brightness profile of stacked galaxy clusters recently measured by SRG/eROSITA and the corresponding predictions from the Magneticum cosmological hydrodynamical simulations, which are known to reproduce other scaling relations observed for massive galaxy clusters. A significant difference between the observed and simulated profiles is present in the very central region, where effective implementation of the AGN feedback likely results in excessive gas redistribution within the core. The simulations predict a very noisy surface brightness profile beyond several times the virial radius of the cluster, with the mean signal being orders of magnitude lower than the local radially-flat but strongly fluctuating emission background, meaning that a proper detection of this component would be very challenging even with larger samples in the future.

The equations of reduced magnetohydrodynamics (RMHD) isolate the Alfvénic energy transfer and turbulence dynamics from MHD in a computationally tractable way. In this study, we derive the equations of RMHD for a low $\beta$ plasma in a dipole coordinate system aligned with an inhomogeneous background that is general enough to represent the Earth's magnetosphere using a multiscale analysis and the Kreiss theorem. The most important effect beyond homogeneous RMHD is the propensity for background Alfvén speed gradients to drive nonlinear wave effects. This work has immediate application to the magnetosphere-ionosphere coupling problem in the Earth's magnetosphere, where the Alfvén speed varies by an order of magnitude over a short distance. We estimate the turbulent energy transfer driven by this. In Earth's magneotsphere, a substantial portion of energy ($>20\%$) could be transferred in this way along auroral field lines. A revised field aligned current density mapping technique to account for this energy loss mechanism is proposed to replace using $j_\parallel/B_0$ being constant along the field line. We also predict the existence of a “saturation current density,” where there is a maximum $j_\parallel$ that exist before driving a nonlinear cascade. At Earth, this value is $\sim 5\; \mu \text{A}/\text{m}^2$ at the ionosphere, which corresponds to the maximum observed value by ground magnetometers. Furthermore, this study makes use of a novel methodology, a computer algebra system, in performing algebraic work under complicated coordinate systems. We hope this approach serves as a template for performing reproducible and verifiable multiscale perturbation analysis under arbitrarily complex geometries.

We propose a Multi-Resonant Double-barrier Quantum-dot-in-a-Well (MR-DWELL) dosimeter with a tunable trade-off between sensitivity and radiation tolerance, realized through graphene-assisted electrostatic screening. The sensing mechanism relies on radiation-induced trapped charge that shifts and broadens resonant tunneling states in the DWELL heterostructure. The~dimensionless capacitance ratio $\eta=C_Q/C_{\mathrm{geo}}$ is introduced as the universal design parameter: it~controls the screening factor $S=\eta/(1+\eta)$ and thereby the trade-off between sensitivity and radiation hardness. For $\eta=2.09$ the effective low-dose shift coefficient is reduced threefold (from $0.14$~to $0.045~\mathrm{meV/mGy}$), while the screened architecture retains $\sim\!83\%$ of the peak tunneling current and a peak-to-valley ratio $\sim\!10$ after $1~\mathrm{MGy}$, thereby preserving the dosimetric sensitivity required for practical readout. The~second-derivative spectroscopy $d^2I/dV^2$ is identified as a robust experimental readout. A~reduced-order Landauer model calibrated against literature data is employed for the screening physics, while a self-consistent NEGF-Poisson-trap framework is formulated for future quantitative validation. Explicit design rules for three operating regimes (high sensitivity, balanced, maximum hardness) are provided, together with a three-population trap model that conceptually enables dose-rate discrimination in the FLASH radiotherapy regime. A~comparative analysis of model vintages and their methodological foundations is included to guide interpretation of numerical predictions.

We present an experimental and numerical investigation of the quality factor degradation ($\Delta Q$) due to pump phase modulation and pump relative intensity noise (RIN) in single- and double-pumped fiber optical parametric amplifiers (FOPAs). These penalties are investigated in FOPAs constructed with fibers having constant and randomly varying zero-dispersion wavelength ($\lambda_0$) along the fiber. We show that pump phase modulation in uniform fibers (constant $\lambda_0$) produces large $Q$ penalties, while in fibers with variations of $\lambda_0$, these penalties can be strongly reduced in both single- and double-pumped FOPAs. We also show that $Q$ penalties due to pump phase modulation tend to disappear in FOPAs made with very short fibers ($L<0.1~\mathrm{km}$) and very low dispersion slope $ S_0 < 0.002~ \mathrm{ps}\, \mathrm{nm}^{-2}\, \mathrm{km}^{-1}. $ The $Q$ penalties due to pump RIN, which for typical FOPA parameters are much smaller than those due to pump phase modulation, are also reduced in non-uniform fibers (varying $\lambda_0$), but do not depend on fiber length nor on fiber dispersion slope.